Quantifying Data Debt: Measuring the Long-Term Cost of Poor Data Practices

In many organisations, data behaves like a growing forest—lush, complex, and full of potential. Yet without careful stewardship, weeds of inconsistency, duplication, and inaccuracy begin to choke its roots. What starts as a small tangle of neglected records eventually becomes an impenetrable thicket—slowing decision-making, distorting insights, and burdening innovation. This overgrowth is what experts call…

The methods of Data Cleaning in Data Science

Introduction Data cleaning is a critical step in the data science workflow. It ensures that the data used for analysis is accurate, consistent, and reliable. Data cleaning is an essential first step in  any data analysis process and is a basic topic covered in any entry-level Data Scientist Course. Advanced courses might include advanced techniques…